Graduate Analytics Engineer in London

Graduate Analytics Engineer in London

London Entry level 30000 - 40000 £ / year (est.) Home office (partial)
Lendable

At a Glance

  • Tasks: Contribute to data models and improve analytics for credit decisions and portfolio analysis.
  • Company: Join Lendable, a fast-growing fintech unicorn on a mission to revolutionise credit.
  • Benefits: Flexible working, health coverage, office meals, and a vibrant team culture.
  • Other info: Exciting growth opportunities in a supportive team with a modern tech stack.
  • Why this job: Make a real impact in a dynamic environment while developing your analytics skills.
  • Qualifications: Solid SQL skills and a collaborative mindset; experience with dbt is a plus.

The predicted salary is between 30000 - 40000 £ per year.

hackajob is collaborating with Lendable to connect them with exceptional professionals for this role.

About Lendable

Lendable is on a mission to build the world's best technology to help people get credit and save money. We're building one of the world’s leading fintech companies and are off to a strong start:

  • One of the UK’s newest unicorns with a team of just over 700 people
  • Among the fastest-growing tech companies in the UK
  • Profitable since 2017
  • Backed by top investors including Balderton Capital and Goldman Sachs
  • Loved by customers with the best reviews in the market (4.9 across 10,000s of reviews on Trustpilot)

So far, we’ve rebuilt the Big Three consumer finance products from scratch: loans, credit cards and car finance. We get money into our customers’ hands in minutes instead of days. We’re growing fast, and there’s a lot more to do: we’re going after the two biggest Western markets (UK and US) where trillions worth of financial products are held by big banks with dated systems and painful processes.

Join us if you want to:

  • Take ownership across a broad remit. You are trusted to make decisions that drive a material impact on the direction and success of Lendable from day 1
  • Work in small teams of exceptional people, who are relentlessly resourceful to solve problems and find smarter solutions than the status quo
  • Build the best technology in-house, using new data sources, machine learning and AI to make machines do the heavy lifting

We're looking for a Junior Analytics Engineer to join the analytical foundation for our US Cards team, the fastest-developing area of the business. In this role, you’ll work closely with analysts, product teams, backend engineers, and business stakeholders to help improve how data is structured, transformed, and consumed across the company. The role is fundamentally about contributing to a strong analytical foundation: helping teams move from question to insight quickly, while improving data quality, scalability, and maintainability. You'll be supported by experienced engineers and given the space to grow — picking up new skills, deepening your SQL and dbt knowledge, and building confidence across a modern data stack.

What you'll be doing:

  • Contributing to the data models that support credit decisions, origination, portfolio analysis, and investor reporting.
  • Building and improving dbt models and transformations, guided by senior engineers and in close collaboration with analysts and stakeholders.
  • Acting as a bridge between analysts, backend engineers, product teams, and the data platform team to help ensure data is modelled and used effectively.
  • Identifying opportunities to improve the efficiency, reliability, and cost-effectiveness of our transformation pipeline over time.
  • Supporting the scaling of our data infrastructure as the business grows.

Our modern data stack:

You’ll work with a modern analytics stack centred around SQL, Snowflake, dbt, Fivetran and Claude.

What we're looking for:

We're looking for someone with solid analytics engineering fundamentals - or the drive to develop them - and the curiosity to apply them in a fast-moving environment. More specifically, we’re looking for:

Essential:

  • Solid SQL skills and a willingness to keep improving them.
  • Some hands-on experience with dbt or ELT pipelines.
  • A collaborative working style and clear communication across technical and non-technical stakeholders.
  • A growing understanding of data modelling and how analytical datasets should be structured for reliability and usability.
  • Comfort using AI tools to move faster and improve the quality of your work.

Desirable:

  • Experience with Snowflake or another modern cloud data warehouse.
  • An interest in learning from and eventually supporting analysts through shared patterns and good practices.
  • Fintech or scale-up experience.

Interview process:

  • Initial call
  • Take Home Task
  • Technical Interview
  • Culture Interview

Life at Lendable:

  • Winning team: the opportunity to scale up one of the world’s most successful fintech companies
  • Flexible working: flexible approach tailored to each role. Hybrid roles require three days in-office weekly; fully remote roles include regular opportunities for in-person connection through socials and off-sites
  • Socials & connection: opportunities and events to come together, socialise, and get to know each other beyond the office walls
  • Health coverage: support for your physical and mental wellbeing, including private health cover
  • Retirement & savings: long-term financial wellbeing through retirement savings plans
  • Employee referral programme: earn a competitive bonus when you refer successful new team members
  • Office meals & snacks: enjoy a fully stocked kitchen, plus complimentary lunches prepared by in-house chefs on in-office days at select locations
  • Sustainable commuting: cycle-to-work and electric vehicle salary sacrifice schemes available in select locations

Please note: The availability and details of specific benefits vary by location and role. For more information, please speak to your Talent Partner.

Lendable

Contact Details:

Lendable Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Graduate Analytics Engineer in London

Embrace Online Competitions

Get involved in online data science competitions like Kaggle or DrivenData. These platforms not only let you showcase your skills but also help you build a portfolio that stands out to hiring companies like Lendable when you're aiming for that entry-level role.

Join Data Science Meetups

Look for local data science meetups or workshops happening in your area. These are perfect for connecting with industry professionals and fellow newbies, giving us the chance to learn the ropes and get our foot in the door at companies like Lendable.

Networking Through University Career Services

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Spotlight Your Skills Online

Create a strong online presence by sharing your projects and insights on platforms like GitHub or LinkedIn. Make sure to apply directly through Lendable’s career page, where your unique skills can shine in their entry-level data science openings!

We think you need these skills to ace Graduate Analytics Engineer in London

SQL
dbt
Data Modelling
Collaboration
Communication Skills
Analytical Skills
AI Tools

Some tips for your application 🫡

Show Off Your Data Skills:As you're aiming for an entry-level data science role at Lendable, don't forget to highlight your proficiency in programming languages like Python or R. Dive into your CV and mention any relevant projects or coursework that demonstrate your data analysis skills or machine learning knowledge.

Include Relevant Projects:If you've done any data-related projects, whether in your studies or during a personal quest, showcase them in a portfolio. This gives us a tangible sense of your capabilities and shows your hands-on experience with data manipulation, visualisation, or model building.

Tailor Your Cover Letter:When crafting your cover letter, make sure to express your enthusiasm for data science and how this role at Lendable aligns with your career goals. Consider sharing why you’re drawn to data-driven decision-making and how you see yourself growing in this field.

Show Your Curiosity:In the data science world, curiosity is key! Mention any online courses or certifications you've pursued that complement your studies. This could be anything from a statistics certification to a data visualisation workshop. It shows us you're serious about learning and growing in this field.

How to prepare for a job interview at Lendable

Brush Up on Your Statistics

For a data science role, the interview may involve some statistical questions or problems. Make sure you're comfortable with concepts like probability, distributions, and hypothesis testing. This will not only help you answer questions but also show your analytical thinking.

Get Hands-On with Tools

Familiarise yourself with popular data science tools like Python, R, and SQL. If you're asked about specific projects, be ready to discuss the tools you used and how they contributed to your analysis. Showing that you not only know the theory but can apply it is essential!

Showcase Relevant Projects

As an entry-level candidate, your portfolio is crucial. Bring along examples of data projects you've worked on, whether during your studies or personal projects. Discuss the challenges you faced and how you overcame them, highlighting your problem-solving skills.

Prepare for Case Studies

Entry-level interviews in data science often include case studies where you'll have to analyse a dataset or solve a problem on the spot. Try out some practice case studies beforehand, so you're not caught off guard. It's all about displaying your thought process and how you tackle data-driven challenges!